This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Airborne transmission represents one of the most rapidly spreading and least understood dissemination mechanisms for pathogens. Some of the most severe viral infections such as Influenza are spread by air. Influenza has caused three pandemics in the last century alone, with an overall death toll reaching tens of millions, and continues to cause annual epidemics of varying severity worldwide. The threat of another pandemic is increasing with the emergence of avian influenza strains in Asia. Public health strategies to prevent and control the often explosive outbreaks associated with these pathogens are limited to vaccination and treatment, if available, or isolation and barrier precautions. The latter includes the utilization of face masks to interrupt the chain of transmission. However, the scientific evidence regarding the efficacy of face masks has been solely based on studies using manikin heads. In continuation of our previous work with rhinovirus we propose to (1) adapt our existing model for airborne dispersal to live attenuated Influenza vaccine viruses (FluMist[unreadable][unreadable] vaccine), (2) determine the route of transmission, and (3) evaluate the effectiveness of surgical masks and N95 respirators, commonly used for protection of healthcare workers. This project is the first attempt to develop a method for evaluation of the utility and efficacy of face masks using viable Influenza virus strains in human subjects. The preliminary data generated in this project will confirm the feasibility of the study design, and, therefore, strengthen a R01 submission concerning the efficacy of established infection control measures for workers in the healthcare setting.